Chinese semiconductor thread II
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Associate Professor Wang Cheng of City University of Hong Kong and his team collaborated with researchers from the Chinese University of Hong Kong to develop microwave photonic chips with faster processing speed and lower energy consumption using lithium niobate as a platform, which can use optics for ultra-fast analog electronic signal processing and calculations. .
According to reports, this chip is 1,000 times faster than traditional electronic processors, consumes less energy, and has a wide range of applications, covering 5/6G wireless communication systems, high-resolution radar systems, artificial intelligence, computer vision, and image and video processing .
Tachyon chips achieve this outstanding performance through an integrated microwave photonic processing engine based on a thin-film lithium niobate platform that performs multi-purpose processing and calculations of analog signals.
The upstream of the optical module industry is mainly manufacturers of optical devices, optical chips, electrical chips, PCBs and structural parts, as well as optical module packaging and testing equipment suppliers. Downstream are mainly communication equipment manufacturers. Telecom equipment and data communication equipment used in optical modules are mainly used in 5G, optical fiber broadband, data centers, consumer electronics, autonomous driving and other fields.
The research team has developed a world-leading microwave photonic chip that is 1,000 times faster than existing processors. Therefore, from the perspective of the optical module industry chain, optical chip technology is in the upstream link of the industry chain.
The research results of Wang Cheng's team not only opened up a new research field, namely lithium niobate microwave photonics, making microwave photonic chips smaller, with high signal fidelity and low latency performance, but also are the basis for chip-level analog electronic processing and computing engines. breakthrough.
According to reports, this chip is 1,000 times faster than traditional electronic processors, consumes less energy, and has a wide range of applications, covering 5/6G wireless communication systems, high-resolution radar systems, artificial intelligence, computer vision, and image and video processing .
Tachyon chips achieve this outstanding performance through an integrated microwave photonic processing engine based on a thin-film lithium niobate platform that performs multi-purpose processing and calculations of analog signals.
The upstream of the optical module industry is mainly manufacturers of optical devices, optical chips, electrical chips, PCBs and structural parts, as well as optical module packaging and testing equipment suppliers. Downstream are mainly communication equipment manufacturers. Telecom equipment and data communication equipment used in optical modules are mainly used in 5G, optical fiber broadband, data centers, consumer electronics, autonomous driving and other fields.
The research team has developed a world-leading microwave photonic chip that is 1,000 times faster than existing processors. Therefore, from the perspective of the optical module industry chain, optical chip technology is in the upstream link of the industry chain.
The research results of Wang Cheng's team not only opened up a new research field, namely lithium niobate microwave photonics, making microwave photonic chips smaller, with high signal fidelity and low latency performance, but also are the basis for chip-level analog electronic processing and computing engines. breakthrough.
This technology is going to trounce nvidia AI chips easily.
While the consumer smart projector market in China is dominated by super cheap 1LCD projectors, DLP does have about 25% of a large market that didn't exist until quite recently. Most 'name brand' Chinese smart projectors use DLP. Outside the home theater projector market, LCoS also has applications in AR.
Map of photoresist companies as 2024
Chinese semiconductor industry
I call upon our experts here: is this really as important as it is being described or is this your usual SCMP hype...
www.sinodefenceforum.com
Chinese semiconductor industry
I call upon our experts here: is this really as important as it is being described or is this your usual SCMP hype...
www.sinodefenceforum.com
Chinese semiconductor industry
https://www.laoyaoba.com/n/865052 Chinese toolmakers got 6 out of 8 bids this week...
www.sinodefenceforum.com
Chinese semiconductor industry
I doubt. Towers could be subjected to sanctions if Chinese firms buy it. I just think China and US just enjoy poking each other eye....
www.sinodefenceforum.com
Chinese semiconductor industry
BOE ordered 55m RMB of Micro LED equipment from NAURA including PECVD & ICP. 5m of which is for GaN production https://www.eet-china.com/mp/a277451.html to be used in this 华灿 Micro LED production, packaging & testing plant
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Chinese semiconductor industry
havoc：首台样机21年6月就完成了。光刻机是02重大专项的子课题，由谁来验收可以参考当年90nm光刻机的验收情况。 The first prototype of immersion DUV was completed in June 21. The lithography machine is a sub-project of the 02 major special project. Who will check and accept it can refer to the acceptance of the 90nm lithography machine in that year.
www.sinodefenceforum.com
Chinese semiconductor industry
havoc：首台样机21年6月就完成了。光刻机是02重大专项的子课题，由谁来验收可以参考当年90nm光刻机的验收情况。 The first prototype of immersion DUV was completed in June 21. The lithography machine is a sub-project of the 02 major special project. Who will check and accept it can refer to the acceptance of the 90nm lithography machine in that year.
www.sinodefenceforum.com
Is just me or all Bloomberg articles about semiconductor in China looks the same no matter who wrote the article.
-Click bait headline like if you are paying to read something new.
-X company is using US technology do Y. Like if X company is suppose to throw US equipment to the sea.
- Unnamed source.
-Paragraph after paragraph full non nonsensical jargon, zero technical information, not specifications or type of equipment or for whatever they are using for.
-Biden administration.
-China military ambitions.
-More sanctions.
Michael Bloomberg could pay 20 bucks a month for an GPT4 account, fire these "Experts" and save some money. The poor guy is getting robbed.
-Click bait headline like if you are paying to read something new.
-X company is using US technology do Y. Like if X company is suppose to throw US equipment to the sea.
- Unnamed source.
-Paragraph after paragraph full non nonsensical jargon, zero technical information, not specifications or type of equipment or for whatever they are using for.
-Biden administration.
-China military ambitions.
-More sanctions.
Michael Bloomberg could pay 20 bucks a month for an GPT4 account, fire these "Experts" and save some money. The poor guy is getting robbed.
SMIC's "Semiconductor Structure and Formation Method" Patent Announced
Changxin Memory’s patent for “a semiconductor structure and its manufacturing method” is published
BOE patent for “folding shaft, display device, and bending test device” published
Changxin Memory’s patent for “a semiconductor structure and its manufacturing method” is published
BOE patent for “folding shaft, display device, and bending test device” published
Huawei is looking at reservoir computing. Might be an indicator of what direction they're going for.
Abstract
Reservoir computing originates in the early 2000s, the core idea being to utilize dynamical systems as reservoirs (nonlinear generalizations of standard bases) to adaptively learn spatiotemporal features and hidden patterns in complex time series. Shown to have the potential of achieving higher-precision prediction in chaotic systems, those pioneering works led to a great amount of interest and follow-ups in the community of nonlinear dynamics and complex systems. To unlock the full capabilities of reservoir computing towards a fast, lightweight, and significantly more interpretable learning framework for temporal dynamical systems, substantially more research is needed. This Perspective intends to elucidate the parallel progress of mathematical theory, algorithm design and experimental realizations of reservoir computing, and identify emerging opportunities as well as existing challenges for large-scale industrial adoption of reservoir computing, together with a few ideas and viewpoints on how some of those challenges might be resolved with joint efforts by academic and industrial researchers across multiple disciplines.
Abstract
Reservoir computing originates in the early 2000s, the core idea being to utilize dynamical systems as reservoirs (nonlinear generalizations of standard bases) to adaptively learn spatiotemporal features and hidden patterns in complex time series. Shown to have the potential of achieving higher-precision prediction in chaotic systems, those pioneering works led to a great amount of interest and follow-ups in the community of nonlinear dynamics and complex systems. To unlock the full capabilities of reservoir computing towards a fast, lightweight, and significantly more interpretable learning framework for temporal dynamical systems, substantially more research is needed. This Perspective intends to elucidate the parallel progress of mathematical theory, algorithm design and experimental realizations of reservoir computing, and identify emerging opportunities as well as existing challenges for large-scale industrial adoption of reservoir computing, together with a few ideas and viewpoints on how some of those challenges might be resolved with joint efforts by academic and industrial researchers across multiple disciplines.